Health examination method for plant seedlings by using spectral analysis

Abstract

The invention discloses a health examination method for plant seedlings by using spectral analysis and relates to a detecting method for chlorophyll of the plant seedings. A Raman spectrum image detecting platform is utilized for detecting the content of chlorophyll under the stresses of different alkali base solutions. The health examination method has the benefits that no chemical reagent is used, the detecting cost is lowered, and pollution to environment can not be caused; Raman spectrum analysis is adopted, complex treatments to samples are not required, the effect of zero-damage identification can be achieved, and experimental data is accurate and quick; by modeling a neural network, influences caused by a large number of different mediums on chlorophyll of the plant seedings can be treated, and the time is saved; experiments can be achieved quickly, accurately, stably and real time, and a great breakthrough is brought to experiment researches to the growth of the plant seedlings.

Description

technical field [0001] The invention relates to a method for detecting chlorophyll of plant seedlings, in particular to a physical examination method for plant seedlings by spectral analysis. technical background [0002] Chlorophyll is one of the most important pigments related to photosynthesis. Photosynthesis is the process of converting light energy into chemical energy by synthesizing some organic compounds. Chlorophyll is present in virtually all photosynthetic organisms, including green plants, prokaryotic blue-green algae (cyanobacteria), and eukaryotic algae. Chlorophyll absorbs energy from light, which is then used to convert carbon dioxide into carbohydrates. Therefore, the amount of chlorophyll indicates the growth state and health of the plant, and the composition of the culture solution is adjusted according to the indicated value. [0003] The growth of plants is a complex physiological, biochemical and material metabolism process. The variation of plant le...

AI Technical Summary

Problems solved by technology

However, when using near-infrared spectroscopy to detect a plant sample, the sample to be detected needs to be subjected to complex cutting and grinding before observation. This method not only destroys the original appearance of the plant, but also cannot carry out continuous sample detection. , because the components in the plants exposed to the outside are easy to reflect with some substances in the air, so that the detected spectral information is inaccurate and there are differences

Moreover, for infrared spectroscopy, the detection of chlorophyll is not very sensitive, and the detection of chlorophyll cannot be realized quickly and effectively.

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